Unresolved stellar companions with Gaia DR2 astrometry

ABSTRACT For stars with unresolved companions, motions of the centre of light and that of mass decouple, causing a single-source astrometric model to perform poorly. We show that such stars can be easily detected with the reduced χ2 statistic, or renormalized unit weight error (RUWE), provided as part of Gaia DR2. We convert RUWE into the amplitude of the image centroid wobble, which, if scaled by the source distance, is proportional to the physical separation between companions (for periods up to several years). We test this idea on a sample of known spectroscopic binaries and demonstrate that the amplitude of the centroid perturbation scales with the binary period and the mass ratio as expected. We apply this technique to the Gaia DR2 data and show how the binary fraction evolves across the Hertzsprung–Russell diagram. The observed incidence of unresolved companions is high for massive young stars and drops steadily with stellar mass, reaching its lowest levels for white dwarfs. We highlight the elevated binary fraction for the nearby blue stragglers and blue horizontal branch stars. We also illustrate how unresolved hierarchical triples inflate the relative velocity signal in wide binaries. Finally, we point out a hint of evidence for the existence of additional companions to the hosts of extrasolar hot Jupiters.</jats:p

Complete nucleotide sequences and genome organization of a cherry isolate of cherry leaf roll virus

The complete nucleotide sequence of cherry leaf roll virus (CLRV, genus Nepovirus) from a naturally infected cherry tree (Prunus avium cv. Bing) in North America was determined. RNA1 and RNA2 consist of 7,893 and 6,492 nucleotides, respectively, plus a poly-(A) tail. Each RNA encodes a single potential open reading frame. The first 657 nucleotides of RNA1 and RNA2 are 99% identical and include the 5′-UTR and the first 214 deduced amino acids of the polyproteins following the first of two in-frame start codons. Phylogenetic analysis reveals close relationships between CLRV and members of subgroup C of the genus Nepovirus

The impacts of climate change across the globe: a multi-sectoral assessment

The overall global-scale consequences of climate change are dependent on the distribution of impacts across regions, and there are multiple dimensions to these impacts.This paper presents a global assessment of the potential impacts of climate change across several sectors, using a harmonised set of impacts models forced by the same climate and socio-economic scenarios. Indicators of impact cover the water resources, river and coastal flooding, agriculture, natural environment and built environment sectors. Impacts are assessed under four SRES socio-economic and emissions scenarios, and the effects of uncertainty in the projected pattern of climate change are incorporated by constructing climate scenarios from 21 global climate models. There is considerable uncertainty in projected regional impacts across the climate model scenarios, and coherent assessments of impacts across sectors and regions therefore must be based on each model pattern separately; using ensemble means, for example, reduces variability between sectors and indicators. An example narrative assessment is presented in the paper. Under this narrative approximately 1 billion people would be exposed to increased water resources stress, around 450 million people exposed to increased river flooding, and 1.3 million extra people would be flooded in coastal floods each year. Crop productivity would fall in most regions, and residential energy demands would be reduced in most regions because reduced heating demands would offset higher cooling demands. Most of the global impacts on water stress and flooding would be in Asia, but the proportional impacts in the Middle East North Africa region would be larger. By 2050 there are emerging differences in impact between different emissions and socio-economic scenarios even though the changes in temperature and sea level are similar, and these differences are greater in 2080. However, for all the indicators, the range in projected impacts between different climate models is considerably greater than the range between emissions and socio-economic scenarios

HABITAT: A longitudinal multilevel study of physical activity change in mid-aged adults

Purpose. To explore the role of the neighborhood environment in supporting walking Design. Cross sectional study of 10,286 residents of 200 neighborhoods. Participants were selected using a stratified two-stage cluster design. Data were collected by mail survey (68.5% response rate). Setting. The Brisbane City Local Government Area, Australia, 2007. Subjects. Brisbane residents aged 40 to 65 years. Measures. Environmental: street connectivity, residential density, hilliness, tree coverage, bikeways, and street lights within a one kilometer circular buffer from each resident’s home; and network distance to nearest river or coast, public transport, shop, and park. Walking: minutes in the previous week categorized as < 30 minutes, ≥ 30 < 90 minutes, ≥ 90 < 150 minutes, ≥ 150 < 300 minutes, and ≥ 300 minutes. Analysis. The association between each neighborhood characteristic and walking was examined using multilevel multinomial logistic regression and the model parameters were estimated using Markov chain Monte Carlo simulation. Results. After adjustment for individual factors, the likelihood of walking for more than 300 minutes (relative to <30 minutes) was highest in areas with the most connectivity (OR=1.93, 99% CI 1.32-2.80), the greatest residential density (OR=1.47, 99% CI 1.02-2.12), the least tree coverage (OR=1.69, 99% CI 1.13-2.51), the most bikeways (OR=1.60, 99% CI 1.16-2.21), and the most street lights (OR=1.50, 99% CI 1.07-2.11). The likelihood of walking for more than 300 minutes was also higher among those who lived closest to a river or the coast (OR=2.06, 99% CI 1.41-3.02). Conclusion. The likelihood of meeting (and exceeding) physical activity recommendations on the basis of walking was higher in neighborhoods with greater street connectivity and residential density, more street lights and bikeways, closer proximity to waterways, and less tree coverage. Interventions targeting these neighborhood characteristics may lead to improved environmental quality as well as lower rates of overweight and obesity and associated chromic disease

Using Time-Resolved Fluorescence to Measure Serum Venom-Specific IgE and IgG

We adapted DELFIA™ (dissociation-enhanced lanthanide fluoroimmunoassay), a time resolved fluorescence method, to quantitate whole venom specific and allergenic peptide-specific IgE (sIgE), sIgG1 and sIgG4 in serum from people clinically allergic to Australian native ant venoms, of which the predominant cause of allergy is jack jumper ant venom (JJAV). Intra-assay CV was 6.3% and inter-assay CV was 13.7% for JJAV sIgE. DELFIA and Phadia CAP JJAV sIgE results correlated well and had similar sensitivity and specificity for the detection of JJAV sIgE against intradermal skin testing as the gold standard. DELFIA was easily adapted for detecting sIgE to a panel of other native ant venoms

Dry weather induces outbreaks of human West Nile virus infections

<p>Abstract</p> <p>Background</p> <p>Since its first occurrence in the New York City area during 1999, West Nile virus (WNV) has spread rapidly across North America and has become a major public health concern in North America. By 2002, WNV was reported in 40 states and the District of Columbia with 4,156 human and 14,539 equine cases of infection. Mississippi had the highest human incidence rate of WNV during the 2002 epidemic in the United States. Epidemics of WNV can impose enormous impacts on local economies. Therefore, it is advantageous to predict human WNV risks for cost-effective controls of the disease and optimal allocations of limited resources. Understanding relationships between precipitation and WNV transmission is crucial for predicting the risk of the human WNV disease outbreaks under predicted global climate change scenarios.</p> <p>Methods</p> <p>We analyzed data on the human WNV incidences in the 82 counties of Mississippi in 2002, using standard morbidity ratio (SMR) and Bayesian hierarchical models, to determine relationships between precipitation and human WNV risks. We also entertained spatial autocorrelations of human WNV risks with conditional autocorrelative (CAR) models, implemented in WinBUGS 1.4.3.</p> <p>Results</p> <p>We observed an inverse relationship between county-level human WNV incidence risk and total annual rainfall during the previous year. Parameters representing spatial heterogeneity in the risk of human exposure to WNV improved model fit. Annual precipitation of the previous year was a predictor of spatial variation of WNV risk.</p> <p>Conclusions</p> <p>Our results have broad implications for risk assessment of WNV and forecasting WNV outbreaks. Assessing risk of vector-born infectious diseases will require understanding of complex ecological relationships. Based on the climatologically characteristic drought occurrence in the past and on climate model predictions for climate change and potentially greater drought occurrence in the future, we suggest that the frequency and relative risk of WNV outbreaks could increase.</p

Global-scale climate impact functions: the relationship between climate forcing and impact

Although there is a strong policy interest in the impacts of climate change corresponding to different degrees of climate change, there is so far little consistent empirical evidence of the relationship between climate forcing and impact. This is because the vast majority of impact assessments use emissions-based scenarios with associated socio-economic assumptions, and it is not feasible to infer impacts at other temperature changes by interpolation. This paper presents an assessment of the global-scale impacts of climate change in 2050 corresponding to defined increases in global mean temperature, using spatially-explicit impacts models representing impacts in the water resources, river flooding, coastal, agriculture, ecosystem and built environment sectors. Pattern-scaling is used to construct climate scenarios associated with specific changes in global mean surface temperature, and a relationship between temperature and sea level used to construct sea level rise scenarios. Climate scenarios are constructed from 21 climate models to give an indication of the uncertainty between forcing and response. The analysis shows that there is considerable uncertainty in the impacts associated with a given increase in global mean temperature, due largely to uncertainty in the projected regional change in precipitation. This has important policy implications. There is evidence for some sectors of a non-linear relationship between global mean temperature change and impact, due to the changing relative importance of temperature and precipitation change. In the socio-economic sectors considered here, the relationships are reasonably consistent between socio-economic scenarios if impacts are expressed in proportional terms, but there can be large differences in absolute terms. There are a number of caveats with the approach, including the use of pattern-scaling to construct scenarios, the use of one impacts model per sector, and the sensitivity of the shape of the relationships between forcing and response to the definition of the impact indicator

Arduous implementation: Does the Normalisation Process Model explain why it's so difficult to embed decision support technologies for patients in routine clinical practice

Background: decision support technologies (DSTs, also known as decision aids) help patients and professionals take part in collaborative decision-making processes. Trials have shown favorable impacts on patient knowledge, satisfaction, decisional conflict and confidence. However, they have not become routinely embedded in health care settings. Few studies have approached this issue using a theoretical framework. We explained problems of implementing DSTs using the Normalization Process Model, a conceptual model that focuses attention on how complex interventions become routinely embedded in practice.Methods: the Normalization Process Model was used as the basis of conceptual analysis of the outcomes of previous primary research and reviews. Using a virtual working environment we applied the model and its main concepts to examine: the 'workability' of DSTs in professional-patient interactions; how DSTs affect knowledge relations between their users; how DSTs impact on users' skills and performance; and the impact of DSTs on the allocation of organizational resources.Results: conceptual analysis using the Normalization Process Model provided insight on implementation problems for DSTs in routine settings. Current research focuses mainly on the interactional workability of these technologies, but factors related to divisions of labor and health care, and the organizational contexts in which DSTs are used, are poorly described and understood.Conclusion: the model successfully provided a framework for helping to identify factors that promote and inhibit the implementation of DSTs in healthcare and gave us insights into factors influencing the introduction of new technologies into contexts where negotiations are characterized by asymmetries of power and knowledge. Future research and development on the deployment of DSTs needs to take a more holistic approach and give emphasis to the structural conditions and social norms in which these technologies are enacte